A Comparative Study of Convolutional Neural Networks and Conventional Machine Learning Models for Lithological Mapping Using Remote Sensing Data

A Comparative Study of Convolutional Neural Networks and Conventional Machine Learning Models for Lithological Mapping Using Remote Sensing Data

Lithological mapping is a critical aspect of geological mapping that can be useful in studying the mineralization potential of a region and has implications for mineral prospectivity mapping. This is a challenging task if performed manually, particularly in highly remote areas that require a large n...

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Bibliographic Details
Main Authors: Hojat Shirmard, Ehsan Farahbakhsh, Elnaz Heidari, Amin Beiranvand Pour, Biswajeet Pradhan, Dietmar Müller, Rohitash Chandra
Format: Article
Language:English
Published: MDPI AG 2022-02-01
Series:Remote Sensing
Subjects:
lithological mapping
remote sensing
machine learning
convolutional neural networks
support vector machines
multilayer perceptron
Online Access:https://www.mdpi.com/2072-4292/14/4/819

Internet

https://www.mdpi.com/2072-4292/14/4/819

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